Use of Analytics in Procurement


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Presented at the 2010 CIPS Australia session on Use of Technology in Procurement. Author: Rajat Dhawan.

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Use of Analytics in Procurement

  1. 1. Did You Know Use of analytical tool increased demand forecast accuracy by 55% - leading to increased contract negotiation power and decreased chances of stocks-outs! © 2010 Accenture. All rights reserved.
  2. 2. Raj Dhawan, PhD Supply Chain Management Accenture The CIPSA Special Interest Forum Use of Technology in Procurement - Sydney PROCUREMENT ANALYTICS © 2010 Accenture. All rights reserved.
  3. 3. Agenda What is Procurement Analytics 1 Why should it be used 2 How can it be implemented 3 © 2010 Accenture. All rights reserved.
  4. 4. Overview – Analytics The process of using quantitative methods to derive actionable insights and outcomes from data.  Involves the capture and use of data to support fact-based decision making and gaining competitive advantage  Typically reporting on what has happened in the past  Using predictive analytics based on historical data to ascertain what will happen in the future WHAT WHY HOW © 2010 Accenture. All rights reserved.
  5. 5. Applications in Procurement  Vendor Evaluation  Factoring complete and timely deliveries, quality of materials, and time and effort to resolution on problematic orders in addition to lowest cost  Spend Analytics  Examine multiple types of data sets (e.g., A/P data, supplier-provided invoice data, tax data), Results in an entirely different look at data elements decrease maverick spend, of spend economies of scale  Demand Forecasting  Average cycle volume, Maximum demand peaks  Contract Management  Optimise discount levels, Forecast financial liabilities WHAT WHY HOW © 2010 Accenture. All rights reserved.
  6. 6. Applications in Procurement  Supplier Relationship Management  vendor score, purchase order value, PO volume  Other examples  vendor consolidation, reducing duplicate orders, increasing contract orders while reducing open market transactions WHAT WHY HOW © 2010 Accenture. All rights reserved.
  7. 7. Source: Competing on Analytics: The New Science of Winning (Davenport / Harris) What? CompetitiveAdvantage Sophistication of Intelligence Optimization Predictive Modeling Forecasting/extrapolation Statistical analysis Alerts Query/drill down Ad hoc reports Standard Reports “What’s the best that can happen?” “What will happen next?” “What if these trends continue?” “Why is this happening?” “What actions are needed?” “What exactly is the problem?” “How many, how often, where?” “What happened?” Predictive Analytics Descriptive Analytics Analytics Sophistication Levels WHAT WHY HOW
  8. 8. Analytics Maturity for Organisations Stage 5 Analytical Competitors Stage 4 Analytical Companies Stage 3 Analytical Aspirations Stage 2 Localized Analytics Stage 1 Analytical Novice Routinely uses analytics as a distinctive capability, takes an enterprise-wide approach, has committed and involved leadership, and has achieved large-scale results. Has established analytical capabilities, and has a few significant initiatives under way – but progress is slow and missing critical elements. Organization lacks one or several of the pre- requisites for serious analytical work. Applies analytics regularly, and realizes benefits across the organization. Pockets of analytical activity, but they are uncoordinated and not focused on strategic targets. WHAT WHY HOW © 2010 Accenture. All rights reserved. WHICH STAGE OF PROCUREMENT ANALYTICS IS YOUR ORGANISATION IN?
  9. 9. Agenda What is Procurement Analytics 1 Why should it be used 2 How can it be implemented 3 © 2010 Accenture. All rights reserved.
  10. 10. - Growing at a terrific rate (a compound annual 60%), speeding up all the time. -Around 1,200 Exabyte of digital data will be generated this year - Information created by machines and used by other machines will probably grow faster than anything else. This is primarily ‘database to database’ information. People are only tangentially involved in most of it.• Increase in computational power will facilitate operations on data thus leading to “fact-based decision- making” Why Analytics is now important WHAT WHY HOW © 2010 Accenture. All rights reserved.
  11. 11. Procurement Analytics Study Based on an analytical (modeling and simulation) technique – Systems Thinking “a holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems.” Motivation for this study To study the effectiveness of Systems Thinking in supply chain scenarios by comparing decisions made with and without the use of the technique. WHAT WHY HOW © 2010 Accenture. All rights reserved.
  12. 12. Basic Setup Tasks Participants Experiment 1. Practitioners provided context and background information on tasks 2. Practitioners divided in two groups – random allocation, 40 each 3. A group of practitioners solve tasks based on their knowledge and information provided 4. The second group is first trained in analytical method (systems thinking). This group uses the analytical tools to solve the tasks. 5. For both the tasks compare the accuracy of results without vs. with the use of Systems Thinking tools WHAT WHY HOW © 2010 Accenture. All rights reserved.
  13. 13. Simple Task The Task • In which quarter did • the Contract Manager have maximum number of contracts on hand? • largest number of contracts expire? • Contract Manager work (signing/expiry) on the least number of Contracts? Context • Inflow of contracts – signing • Outflow of contracts – expiry • Details of inflow and outflow provided for time periods • Manual vs. Visual Solution • Active contracts in any quarter = expired – new contracts from previous quarters + those in current quarter WHAT WHY HOW © 2010 Accenture. All rights reserved. Total active contracts
  14. 14. Simple Task - Results Procurement • How many contracts • Current state of contracts • Expiry/renewal • Reporting WHAT WHY HOW • Even simple, routine tasks can sometimes get overwhelming or not given sufficient attention… • Electronic capture of data, visual representation and alerts go a long way Accuratecalculationoftimeperiodwithlargest contracts(percentageofparticipants) © 2010 Accenture. All rights reserved.
  15. 15. Complex Task The Task • Forecast sales of mobile phones over next two years Context • Telco operating in a new market • Uncertain demand • Historical information • External factors • Sales drives procurement, impacts inventory Solution • Sharp increase in product demand in first 8 months, followed by sharp decrease in the following 10 months and then gradual decline WHAT WHY HOW © 2010 Accenture. All rights reserved.
  16. 16. Complex Task - Results •Naïve mental models • Not taking into account all factors • Not capturing the right causal relationships • Not being able to compute affect of input factors to forecast Out of stock – rush orders, higher purchase price, unhappy business units, unhappy customers, loss of market share Excess stock – inventory holding costs, extra resources for maintenance, increased cost  decrease in profit Accurate Forecast GUT FEEL WHAT WHY HOW © 2010 Accenture. All rights reserved.
  17. 17. Complex Task - Results Procurement • When to order and how many • Accurate information on volume leading to better negotiating power • Lesser chances of going out of stock or having excess • Improved communication with business units and vendors WHAT WHY HOWCorrectforecast(percentageoftotalparticipants) FACT BASED Improved understanding of stocks and flows © 2010 Accenture. All rights reserved.
  18. 18. Summary of Results WHAT WHY HOW © 2010 Accenture. All rights reserved.  Native ability  to comprehend complex procurement issues is limited – too many variables to process  Fact-based decision making  leads to better results – accurate, measurable, resulting in lower costs and greater savings.  Analytical tools  improve our ability to capture right information, process it and help in informed decision making.
  19. 19. Agenda What is Procurement Analytics 1 Why should it be used 2 How can it be implemented 3 © 2010 Accenture. All rights reserved.
  20. 20. How will Analytics support a Procurement Organisation Internal Customer Management Training & Development Supplier Relationship Management Procurement Shared Services Requisition to Pay Systems Source to Contract Systems ENABLERS Other Analytical Tool Source to Contract Requisition to Pay Contract Lifecycle Management Organisation Structure Governance/ Compliance Proc. Performance DEMAND MANAGEMENT SOURCING SUPPLIER MANAGEMENT PROCUREMENT STRATEGY Capture information, generate reports and provide insight Use information and insight for day to day activities – operationalise analytics Use information and insight -monitoring, continuous improvement , one-off decisions WHAT WHY HOW © 2010 Accenture. All rights reserved. 1 3 2
  21. 21. Corporate Funcitons Where does the analytics role fit Category Managers Category Managers Category Managers CPO Procurement Manager Procurement Manager Procurement Shared Services Procurement Manager Human Resources Legal IT Contract Managers Finance WHAT WHY HOW © 2010 Accenture. All rights reserved. Vendor Managers Recruitment, training Financial master data sharing, AP, budgeting Contracts data sharing Data capture, systems support, shared resources, systems integration Strategy and Governance 2. Procurement Analytics Manager • Part of Strat & Gov • Reports to CPO • Makes sense of analysed data, benchmarks • Supports Procurement, Category and Contract managers • Liaises with business units 1. Data Analyst • Part of PSS • Potentially shared / outsourced • Supports Analytics Manager • Ensures data is captured, and joined • Models data, generates forecasts
  22. 22. Focus on value and not on math!  Focus on business benefits  What is the issue, hypothesis and realistic solution. How will this benefit business, help in improving efficiency or add value  Using the right tools  BI, scorecards, what-if scenario analysis, predictive analysis, optimisation  Using the right skill  Business trained analysts, not only from IT WHAT WHY HOW © 2010 Accenture. All rights reserved.
  23. 23. Implementation Challenges  Organisation  Top leadership awareness and support  Partnership with business units  Skill-set not available  Processes  One-off versus Operationalised  Systems  Right technology not available; antiquated  Technology not usable  Data  Data in multiple systems  Data not captured; existing data not analysed WHAT WHY HOW © 2010 Accenture. All rights reserved.
  24. 24. Next Steps  Organisation  Leadership – gain support  BUs – collaborate, share  Skills – develop, hire or share  Culture – fact-based, not just gut- feel decisions  Process  Embed analytics in processes WHAT WHY HOW  Systems  Short-term – integrate, consolidate & fully utilise existing systems  Long-term – invest in an eprocurement suite and specialised analytical tools
  25. 25. Summary  Procurement Analytics is the use of data to gain insight into what has happened, and more importantly – what may happen – to better manage spend, contracts, vendors and internal customers.  There is now ample data, and technology that is usable by procurement staff, to gain such insights.  Evidence suggests that, analytical tools, when used appropriately by skilled users, are able to facilitate fact-based decision making.  Procurement leadership needs to instill a culture of fact-based decision making at all levels of procurement.  Procurement staff needs to be provided support via appropriate tools and skills to fully leverage Analytics. © 2010 Accenture. All rights reserved. WHAT WHY HOW
  26. 26. 0402 925 505 © 2010 Accenture. All rights reserved.